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Statistical advisory service at Rigshospitalet – University of Copenhagen

Section of Biostatistics > Statistical advisory s...

Statistical advisory service at Rigshospitalet

What can we assist with

Any type of  statistical problem in relation to planning a study, choosing and applying the appropriate statistical tools, and understanding results. This includes

  • Study design (type of design and sample size)
  • Statistical analysis (choice of analysis, execution of analysis  via dedicated statistical software, interpretation and reporting of results) 

Note that we are only able to offer very limited help with dedicated data management such as data cleaning and data base programming

Who is eligible for help

Researchers and research groups at Copenhagen University Hospital and Glostrup Hospital. 

PhD-students and employees at the Faculty of Health and Medicinal Sciences are requested to use our regular advisory service :

How to get help

Write an email to 
containing a brief description of your problem. Emails are handled on a weekly basis each Friday, so you can expect to receive a response to your request within a week.

How much help can you get

This is judged from a case to case basis entirely at the discretion of the statistical consultant handling your request. For larger commitments additional funding may be necessary. 

If the consultant provides substantial input for a paper in terms of analyses, interpretation of results, and drafting of the paper, then co-authorship is only natural and expected. See also the Vancouver Protocol.

Examples of specific questions

Question: I have conducted a two sided t-test, but a referee has asked for a non-parametric test in addition. What is this and how do I compute the test?

Question: We are planning an RCT and need to discuss power and statistical analysis plan.

Question: I cannot insert text on a plot created in SAS.

Question: I have conducted a logistic regression, but would like to discuss if I have interpreted the estimates correctly.

Question: We are planning to apply for funding for a larger study, but are in doubt about the best ways to describe and subsequently tackle the statistical challenges.